Regulation of medical products is a public health and safety issue with substantial economic implications. This project presents the first empirical model of approval regulation for new medical devices. Using a unique dataset of all high-risk device approvals since 1970, I explore the evolution of the FDA’s high-risk device regulatory process as well as differences across specialty areas and disease groups. I document several new facts about the regulation of high-risk medical devices: For novel devices, approval times have mostly decreased over recent decades. However, I identify substantial heterogeneity across regulatory categories. For example, while average review times have fallen for novel cardiovascular devices over the past two decades, they have increased for new radiological devices. Next, I develop an empirical model that predicts approval times for devices in different product categories and in different years. I use this model to show that approval times are decreasing in market entry order. That is, the earliest entrants in a product category can expect significantly longer review times than “me too” market entrants. This entry order gradient is precisely the opposite of what has been documented in the market for new pharmaceuticals. As such, the burden of significantly longer regulatory times poses relative disincentives for medical device innovators to pursue novel innovation vs. follow-on innovation.

Regulation of medical products is a public health and safety issue with substantial economic implications. This project presents the first empirical model of approval regulation for new medical devices. Using a unique dataset of all high-risk device approvals since 1970, I explore the evolution of the FDA’s high-risk device regulatory process as well as differences across specialty areas and disease groups. I document several new facts about the regulation of high-risk medical devices: For novel devices, approval times have mostly decreased over recent decades. However, I identify substantial heterogeneity across regulatory categories. For example, while average review times have fallen for novel cardiovascular devices over the past two decades, they have increased for new radiological devices. Next, I develop an empirical model that predicts approval times for devices in different product categories and in different years. I use this model to show that approval times are decreasing in market entry order. That is, the earliest entrants in a product category can expect significantly longer review times than “me too” market entrants. This entry order gradient is precisely the opposite of what has been documented in the market for new pharmaceuticals. As such, the burden of significantly longer regulatory times poses relative disincentives for medical device innovators to pursue novel innovation vs. follow-on innovation.

Thanks for the question! It’s a particularly fitting one because it is part of the discussion in the extended version of this project’s write up.

One recommendation is to encourage both more and earlier dialogue between innovators and regulators. A common complaint among innovators is that they simply do not know what regulators will ask for ex ante and that their negotiations with the FDA often don’t begin until after clinical trials are already underway. Among other things, more and earlier dialogue between device innovators and the FDA would reduce informational uncertainties about the burden of proof expected by regulators in clinical trials.

Another suggestion would be the establishment of more transparent guidelines for clinical trials and defining categories of endpoints for such trials, so that innovators can better plan trials that are likely to meet the FDA’s expectations and clinical evidence requirements.

Neither of the above are mutually exclusive. While devices are very diverse and the specifics of future clinical trials are hard to anticipate, it is also almost certainly the case that more can be done to reduce informational uncertainties around bringing new innovations to market.

I agree that this research has major implications. Could you discuss the other disciplines that students are using in complementary research as part of your larger IGERT? How might one research the barriers to reducing regulatory review of start-up devices?

Thanks for your questions. I hope that my answer above is also useful.

As far as researching barriers to regulatory review goes: I actually do some of this with the data that I already have. Specifically, I can look at differences in the ratios of review staff to new device applications as well as differential policies across different advisory committees (e.g. different policies for those regulating cardiac vs. radiological devices) to start to undersand which scenarios are most conducive to efficient review processes.

I also consider a number of firm-specific effects as well as categories of applicant firms. For example, if there is some learning in the regulatory process, then we should observe more established firms experiencing shortened approval times relative to firms with fewer devices already on the market. Additionally, we should expect to see firms improving their approval rates as well as approval times as they increase their portfolio of successful applications. I am working on testing many of these theories in the next phase of the project.

There are also a number of complementary research topics to this one, including issues around health insurance coverage and reimbursement. Perhaps the most significant one for public finance is that new device approvals by the FDA are often tantamount to Medicare coverage for their use. This means that many new device approvals also amount to additional product availability for publicly insured individuals. The cost implications of these approvals are ambiguous: while some new device approvals are likely to represent very expensive new technologies, other new device approvals (e.g. for diabetes management) have the potential to reduce Medicare expenditures as well as socioeconomic health disparities.

Hi Ariel,
I’m interested in the source of your data set; how were the data collected, under what circumstances, etc. It’s historical breadth is very interesting!
Also, given any number of recent and historical examples of problems with pharmaceutical innovations that had to be withdrawn from the market because of safety issues, should it really be a goal to shorten the time of review before marketing new devices?

Hi Aurora, thanks for your questions.
The data are simply the FDA’s full database of all historical premarket approvals. The FDA wasn’t given a mandate to regulate medical devices until 1976 (when Congress passed the Medical Device Amendments act, which gave the FDA primary authority to regulate devices sold in the US); the database I use is a full catalog of all PMA device approvals since that time. Please also note that the PMA process is one of 3 types of approval processes for new devices and the one that is designated for the highest risk device. To your next question, I have a few points: 1) The focus of this project is on devices rather than pharmaceuticals. 2) There have nevertheless been several medical device recalls in recent years. However, the vast majority of these recalls have been for devices regulated through the less-stringent 510(k) process, rather than the more extensive PMA process, which is the focus of this project (Zuckerman et. al.’s 2011 paper in the Archives of internal medicine is the most recent documentation of this phenomenon). 3) It is absolutely important to weigh greater efficiency against the the public safety risks inherent in medical technology. This project does not make any value judgments at all about the extent to which the latter should be traded off in the interest of the former, so I want to be clear about that. What is the case however, is that conditional on being the kind of device that ultimately gets approval (and is not subsequently withdrawn for safety reasons) it is true that more novel devices experience longer regulatory times than follow-on innovations and this is precisely the opposite of the pattern observed for new chemical drugs.

Interesting work. Are there economic advantages to being the first product approved in terms of market share or time in the market without competition that might offset the disincentive to being first that comes from the PMA process?

Hi Jeffrey, in short: absolutely! However, the implications of my findings are that this period of time in which device manufacturers are the only only producers on the market is necessarily shortened by the dynamics of the approval system, whereas the effective monopoly of the first entrant is effectively EXTENDED in the pharmaceutical industry, where approval times exhibit the opposite pattern. This means that the relative advantage of coming up with a very novel technology is smaller in the medical device industry than elsewhere.

Aurora,
Your findings are interesting and your presentation of information very clear. Thank you. I’m left wondering if conditions for approval in other countries are different and if they are, does it mean that innovative high risk devices are being developed elsewhere at a more rapid rate? And if that is the case, does that mean that the US is losing economically because of its slow to approve policies and the disincentives to be highly initiative? Thanks, g

Hi Gary, great question! In fact, approval times are significantly shorter in the EU than in the US. Kramer et. al. have a 2012 paper in the New England Journal of Medicine on “Regulation of Medical Devices in the United States and European Union” that does a really nice job of outlining differences between the two systems. In short, regulatory times are longer in the US than in other developed countries and that difference has been growing over the past decade. This means that a lot of class 3 devices (in particular, a lot of cardiology devices) reach the European market a few years before they are brought to market in the US. One salient example is the “MitraClip” (for Mitral valve repair), which was approved for use in the EU in March of 2008 and is still awaiting FDA approval. This means that European patients often can benefit from new technologies earlier than US patients. Moreover, since 7 of the 10 largest device manufacturers in the world are US companies and since the US is by far the world’s largest market for medical devices, this also implies delayed profits for device companies.

Laurie Rokakis

Have the number of panels (or committees) that give approval on these devices increased, decreased, or remained the same for the past several decades? Also, what impact do you believe, if any, the internet has had on the overall speed of the approval process?

Hi William,
Thanks for the question! The number of committees has been relatively constant, but the number of high risk devices approved each year has steadily increased over time (there is a scatter plot of this on the poster if you want to have a more detailed look at the annual data). As far as the internet goes, it’s always hard to say what the impact has been, but the review process itself takes place within the FDA (and between the FDA and applicant firms), so the advent of the internet almost certainly has streamlined communications, etc., but I don’t know of any specific ways in which it has changed the nature of the review process itself, which is typically carried out by experienced regulators (e.g. engineers and biostatisticians) within the FDA.
Best,
Ariel